Search query classification

ABSTRACT

Disclosed are various embodiments for classifying search queries. A computing device identifies a user account associated with a submission of a search query to an electronic commerce application. The computing device then identifies a network page provided by the electronic commerce application, wherein the network page is requested with the user account. Subsequently, the computing device classifies the search query based at least in part on the requested network page.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to, and the benefit of, copending U.S.patent application Ser. No. 14/629,570, filed on Feb. 24, 2015, andentitled “SEARCH QUERY CLASSIFICATION,” which is incorporated byreference as if set forth herein in its entirety.

BACKGROUND

Electronic commerce systems may provide search functionality for usersto search for products or items available for sale from an electroniccatalog of the electronic commerce system. This search functionalitymay, for example, allow for users to submit search queries. Users mayalso be able to further sort or otherwise refine the search results thatare returned.

BRIEF DESCRIPTION OF THE DRAWINGS

Many aspects of the present disclosure can be better understood withreference to the following drawings. The components in the drawings arenot necessarily to scale, with emphasis instead being placed uponclearly illustrating the principles of the disclosure. Moreover, in thedrawings, like reference numerals designate corresponding partsthroughout the several views.

FIG. 1 is an illustration of one of several embodiments of the presentdisclosure.

FIG. 2 is a drawing of a networked environment according to variousembodiments of the present disclosure.

FIG. 3 is a flowchart illustrating one example of functionalityimplemented as portions of an application executed in a computingenvironment in the networked environment of FIG. 2 according to variousembodiments of the present disclosure.

FIG. 4 is a flowchart illustrating one example of functionalityimplemented as portions of an application executed in a computingenvironment in the networked environment of FIG. 2 according to variousembodiments of the present disclosure.

FIG. 5 is a schematic block diagram that provides one exampleillustration of a computing environment employed in the networkedenvironment of FIG. 1 according to various embodiments of the presentdisclosure.

DETAILED DESCRIPTION

Disclosed are various embodiments for classifying search queries.Network pages, such as web pages provided by electronic commerceapplications, may provide a search bar, field, or similar user interfaceelement to assist in searching for items in a product catalog. Searchqueries entered in the search bar may cause a list of matching productsor items to be returned by the electronic commerce application. However,users may also wish to find network pages of the electronic commerceapplication that are unrelated to products, such as a help or customerservice network page, a network page with company contact information, anetwork page for managing a user account, and/or similar non-productrelated network pages. In such instances, users may submit a searchquery via the search bar to find the non-product related network pagefor which the user is searching.

In order to provide accurate search results, search queries may beclassified as product search queries, non-product search queries, helpsearch queries, and/or classified as other types of search queries. Thesearch results provided in response to the search query may be based atleast in part on the type or classification of the submitted searchquery. In the following discussion, a general description of the systemand its components is provided, followed by a discussion of theoperation of the same.

Beginning with FIG. 1, shown is a user interface 100, such as a browserwindow or other interface. Within the user interface 100 are displayed anumber of search results 103 rendered in response to submission of asearch query. Also depicted in the user interface 100 is a suggestedsearch result 106. The suggested search result 106 may be included inthe response to a search query if the search query has been determinedto be a search query associated with attempts to find specific content,such as the help section of a network site, instead of a generic searchquery or a default search query, such as a product search querysubmitted to an electronic commerce application.

As illustrated, a search query of “user help” has been previouslysubmitted. The submitted search query, in some embodiments, may bedepicted in an address bar 109, as shown. In response, a number ofsearch results 103 for products or items available for purchase thatmatch the search query “user help” have been returned. However, searchquery “user help” may have been previously classified as a non-productsearch query, such as a help search query. Therefore, a suggested searchresult 106 directing a user to the user help section of the electroniccommerce application is included with the search results 103 in case theuser was looking for the user help section of the electronic commerceapplication instead of search of products that matched the search query“user help.”

With reference to FIG. 2, shown is a networked environment 200 accordingto various embodiments. The networked environment 200 includes acomputing environment 203 and a client device 206, which are in datacommunication with each other via a network 209. The network 209includes, for example, the Internet, intranets, extranets, wide areanetworks (WANs), local area networks (LANs), wired networks, wirelessnetworks, or other suitable networks, etc., or any combination of two ormore such networks. For example, such networks may comprise satellitenetworks, cable networks, Ethernet networks, and other types ofnetworks.

The computing environment 203 may comprise, for example, a servercomputer or any other system providing computing capability.Alternatively, the computing environment 203 may employ a plurality ofcomputing devices that may be arranged, for example, in one or moreserver banks or computer banks or other arrangements. Such computingdevices may be located in a single installation or may be distributedamong many different geographical locations. For example, the computingenvironment 203 may include a plurality of computing devices thattogether may comprise a hosted computing resource, a grid computingresource, and/or any other distributed computing arrangement. In somecases, the computing environment 203 may correspond to an elasticcomputing resource where the allotted capacity of processing, network,storage, or other computing-related resources may vary over time.

Various applications and/or other functionality may be executed in thecomputing environment 203 according to various embodiments. Also,various data is stored in a data store 213 that is accessible to thecomputing environment 203. The data store 213 may be representative of aplurality of data stores 213 as can be appreciated. The data stored inthe data store 213, for example, is associated with the operation of thevarious applications and/or functional entities described below.

The components executed on the computing environment 203, for example,include an electronic commerce application 216, a query classificationapplication 219, a network page server application 223, and otherapplications, services, processes, systems, engines, or functionalitynot discussed in detail herein. The electronic commerce application 216is executed in order to facilitate online purchases of items over thenetwork 209. The electronic commerce application 216 may generatenetwork pages, such as web pages, that provide descriptions of items andallow for purchase of the item. The electronic commerce application 216may also provide search functionality, such as a tool bar, text inputfield, filters, and/or other user interface elements, that facilitatesearching a product catalog for one or more items. The electroniccommerce application 216 may also perform various backend functionsassociated with the online presence of a merchant in order to facilitatethe online purchase of items as will be described. The queryclassification 219 is executed to classify search queries received fromclient devices 206, as will be further described herein. The networkpage server application 223 is executed to dynamically generate networkpages on behalf of the electronic commerce application 216, as will befurther described herein.

The data stored in the data store 213 includes, for example, classifiedsearch queries 226, user accounts 229, network page templates 233, aproduct catalog 236, and potentially other data. The individual ones ofthe classified search queries 226 may correspond to one or more searchquery categories 239 and one or more suggested network pages 243. A useraccount 229 may include one or more requested network pages 246requested with the user account 229 and a submitted search query 249submitted to the electronic commerce application 216 with the useraccount 229. The product catalog may include one or more items 253 forsale through the electronic commerce application 216.

The classified search queries 226 represent the set of search queriesthat have been previously submitted to the electronic commerceapplication 216 and have been classified by the query classificationapplication 219 as belonging to one or more search query categories 239.Each classified search query 226 may be associated with one or moresearch query categories 239 and with a suggested network page 243.

Search query categories 239 represent a type, classification, or othertaxonomy for search queries. Examples of search query categories 239 mayinclude product search queries, which may represent search queriesassociated with searches of the product catalog 236, and non-productsearch queries, which may represent search queries for information notcontained in the product catalog 236. Non-product search queries may,for example, include searches for customer service information, useraccount management information, company contact information, and helpwith using various aspects of the electronic commerce application 216 ingeneral. In some embodiments, a classified search query 226 may beassigned to multiple search query categories 239.

A suggested network page 243 represents a network page or an address fora network page that is likely to be the intended destination of a userof the electronic commerce application 216. For example, a usersubmitting a non-product search query may intend to find the help pageof the electronic commerce application 216 and not network pages ofproducts that match the search term “help.” Therefore, the suggestednetwork page 243 for the non-product search query may represent the helppage of the electronic commerce application 216. In various embodiments,a classified search query 226 may include multiple suggested networkpages 243.

The user accounts 229 may include data or attributes associated with theaccount of a user of the electronic commerce application 216. Such dataor attributes may include, for example, the name, address, phone number,email address, employer, occupation or profession, purchase or orderhistory, demographic data, or other data of the user. Such data orattributes may also include authorization data such as user name,password, personal identification number (PIN), or other similar data.User accounts 229 may also include data for tracking interactions of auser with the electronic commerce application 216, such as any requestednetwork pages 246 and/or a submitted search query 249.

A requested network page 246 represents a request for a network pagesubmitted to the electronic commerce application 216 with the useraccount 229. This may include the address of the requested network page246, as represented by a uniform resource locator (URL) or otheridentifier. This may also include the time that the request was made anddata regarding how the requested network page 246 was reached. Forexample, this may include data indicating that the requested networkpage 246 was reached from a link located on a previously visited networkpage, such as a search results page, and the address of the previouslyvisited network page, as represented by a URL for the previously visitednetwork page.

A submitted search query 249 represents a search query submitted to theelectronic commerce application 216 with the user account 229. This mayinclude the text of the submitted search query 249, the time that thesubmitted search query 249 was received by the electronic commerceapplication 216, the time that the submitted search query 249 was sentfrom a client device 206, and/or potentially other data.

A network page template 233 represents data specifying the layout andcontent of a network page generated by the network page serverapplication 223. A network page template 223 may, for example, specifywhere information for individual items 253 is to be placed in a networkpage generated by the network page server application 223 or wheresearch results generated by the electronic commerce application 216 areto be located in the network page generated by the network page serverapplication 223. The network page template 223 may also specify a theme,style, color scheme, font, and/or details of the network page generatedby the network page server application 223.

A product catalog 236 represents a schema, taxonomy, directory, or otherorganizational scheme for items 253 available for purchase via theelectronic commerce application 216. Items 253 may include goods,services, digital or electronic media, and similar products ormerchandise available for purchases through the electronic commerceapplication 216. Each item 253 has a unique identifier 256 whichuniquely identifies the item 253 from other items 253 listed in theproduct catalog 236. The unique identifier 256 may be a catalog or indexnumber, a Universal Product Code (“UPC”) number, or similar uniquelyidentifying code, number, symbol, or attribute.

The client device 206 is representative of a plurality of client devicesthat may be coupled to the network 209. The client device 206 maycomprise, for example, a processor-based system such as a computersystem. Such a computer system may be embodied in the form of a desktopcomputer, a laptop computer, personal digital assistants, cellulartelephones, smartphones, set-top boxes, music players, web pads, tabletcomputer systems, game consoles, electronic book readers, or otherdevices with like capability. The client device 206 may include adisplay 259. The display 259 may comprise, for example, one or moredevices such as liquid crystal display (LCD) displays, gas plasma-basedflat panel displays, organic light emitting diode (OLED) displays,electrophoretic ink (E ink) displays, LCD projectors, or other types ofdisplay devices, etc.

The client device 206 may be configured to execute various applicationssuch as a client application 263 and/or other applications. The clientapplication 263 may be executed in a client device 206, for example, toaccess network content served up by the computing environment 203 and/orother servers, thereby rendering a user interface 100 on the display259. To this end, the client application 263 may comprise, for example,a browser, a dedicated application, etc., and the user interface 100 maycomprise a network page, an application screen, etc. The client device206 may be configured to execute applications beyond the clientapplication 263 such as, for example, email applications, socialnetworking applications, word processors, spreadsheets, and/or otherapplications.

Next, a general description of the operation of the various componentsof the networked environment 200 is provided. To begin, one or moresearch queries and one or more requests for network pages are receivedby the electronic commerce application 216 from a client application 263associated with a user account 229. Each search query received is storedby the electronic commerce application 216 as a submitted search query249 of the user account 229 and each request for a network page isstored by the electronic commerce application 216 as a requested networkpage 246 of the user account 229.

For each submitted search query 249, the electronic commerce application216 compares the submitted search query 249 with each of the classifiedsearch queries 226 to determine whether the submitted search query 249matches one of the classified search queries 226. If the submittedsearch query 249 matches one of the classified search queries 226, thenthe electronic commerce application 216 retrieves the search querycategories 239 and suggested network pages 243 of the matchingclassified search query 226 and supplies them to the network page serverapplication 223. The network page server application 223 then uses thesearch query categories 239 and the suggested network pages 243 toselect an appropriate network page template 233. The network page serverapplication 223 then generates and returns a network page to the clientapplication 263.

However, if the submitted search query 249 does not match a classifiedsearch query 226, then the electronic commerce application 216 searchesthe product catalog 236 for one or more items 253 that match one or moreterms in the submitted search query 249. The electronic commerceapplication 216 supplies the list of matching items 253 to the networkpage server application 223, which generates a network page thatincludes information about the items 253 in the manner specified byanother network page template 233.

Concurrent with the process described above, the query classificationapplication 219 analyzes the submitted search query 249 forclassification. The query classification application 219 may, forexample, track the number of times that the electronic commerceapplication 216 has received the submitted search query 249, either froma single user account 229 or from multiple user accounts 229. The queryclassification application 219 may also track, for example, the numberof times that users have navigated to a particular requested networkpage 246 after the electronic commerce application 216 has received thesubmitted search query 249. If users have navigated to a particularrequested network page 246 after the electronic commerce application 216has received the submitted search query 249 more often than expected,then the electronic commerce application 216 may add the submittedsearch query 249 to the set of classified search queries 226 by settingthe suggested network page 243 to the particular requested network page246 that is visited more frequently than expected and by assigning asearch query category 239 based upon the type of the particularrequested network page 246 that has been visited more often thanexpected.

For example, a user may submit a search query of “user help.” The usermay then be presented with a network page containing a listing of items253 that match one or more of the search terms in the “user help” query.However, if a user is more interested in finding the help sectionprovided by the electronic commerce application 216, such as a helppage, the user may then search for and follow a link to the help pageinstead of following a link to a network page for one of the items 253.If a greater than expected or predicted number of users follow the linkto the help page after submitting the query “user help,” then the queryclassification application 219 may determine that the query “user help”is not a product search query, but is a non-product search query, suchas a query intended to lead a user to the help page. The queryclassification application 219 may subsequently include the search queryin the list of classified search queries 226 and set the values for thesearch query category 239 and the suggested network page 243accordingly.

Moving next to FIG. 3, shown is a flowchart that provides one example ofthe operation of a portion of the query classification application 219according to various embodiments. It is understood that the flowchart ofFIG. 3 provides merely an example of the many different types offunctional arrangements that may be employed to implement the operationof the portion of the query classification application 219 as describedherein. As an alternative, the flowchart of FIG. 3 may be viewed asdepicting an example of elements of a method implemented in thecomputing environment 203 (FIG. 2) according to one or more embodiments.

Beginning with box 303, the query classification application 219identifies a user account 229 (FIG. 2) associated with a submittedsearch query 249 (FIG. 2) received from a client application 263 (FIG.2), such as a browser or other application. The query classificationapplication 219 may identify the user account 229, for example, bychecking for a cookie, session identifier, or similar identificationtoken included with the submitted search query 249. If a user is notlogged in, however, the user account 229 may be identified through othermeans, such as by internet protocol (IP) address or a browserfingerprint based upon a unique combination of browser plugins, systemfonts, HTTP_ACCEPT headers, user agent, and other information reportedby the browser executing on the client device 206 (FIG. 2) of the user.By identifying a user account 229 to associate with a submitted searchquery 249, the search behavior of individual users may be tracked sothat the submitted search query may be accurately classified, as will bediscussed in further detail herein.

Moving on to box 306, the query classification application 219identifies a requested network page 246 (FIG. 2) associated with theuser account 229. The requested network page 246 may be identified, forexample, by analyzing requests for network pages sent to the electroniccommerce application and/or network page server application 223 (FIG.2). In some embodiments, the query classification application 219 maylimit itself to identifying only requested network pages 246 that wererequested after the submitted search query 249 was received. Suchbehavior may indicate that a user is actively searching for therequested network page 246 by using the submitted search query 249.

Referring next to box 307, the query classification application 219 maydetermine whether the requested network page 246 is a ranked higher thana predefined threshold. For any submitted search query 249, links to anumber of network pages may provided in response. These links to networkpages may be sorted and ranked, for example, according to relevancy,popularity, or some other metric, where links to more relevant orpopular network pages are provided first. By determining whether arequested network page 246 is ranked prior to classifying the submittedsearch query 249 improper or incorrect classifications of the submittedsearch query 249 may be minimized. If the requested network page 246 isranked higher than the threshold, then execution proceeds to box 309.Otherwise, the previously described path of execution subsequently ends.

Proceeding next to box 309, the query classification application 219associates the submitted search query 249 with the requested networkpage 246, strengthening the correlation between the submitted searchquery 249 and the requested network page 246. For example, the queryclassification application 219 may store a correlation between thesubmitted search query 249 and the requested network page 246 if therequested network page 246 is the first network page requested after thesubmitted search query 249 is received by the electronic commerceapplication 216. In some embodiments, the query classificationapplication 219 may store a correlation between the submitted searchquery 249 and the requested network page 246 if the requested networkpage 246 is one of several network pages requested after the submittedsearch query 249 is received by the electronic commerce application 216.For example, the query classification application 219 may identify acorrelation between one of the first two, three, four, five, or otherthreshold number of network pages requested after the submitted searchquery 249 is received by the electronic commerce application 216 and thesubmitted search query 249 itself. In other embodiments, the queryclassification application 219 may store a correlation between thesubmitted search query 249 and the requested network page 246 if therequested network page 246 is requested within a predefined period oftime after the submitted search query 249 is received by the electroniccommerce application 216.

Referring next to box 313, the query classification application 219calculates the probability that the submitted search query 249 wouldlead the user to the requested network page 246 in comparison to othernetwork pages. This probability may be represented, for example by theequation:

P=P(B|A)−P(B)   (1)

where P(B|A) represents the observed probability that a user followedsubmitted search query 249 “A” to requested network page 246 “B” incomparison to those users arrived at requested network page 246 “B”independently. The resulting value “P” represents the associationbetween the submitted search query 249 and the requested network page246. Larger values of “P” may indicate that the submitted search query249 is received from users who are actively searching for the requestednetwork page 246. Other models, which may be used in various embodimentsof the present disclosure, are disclosed in U.S. Pat. No. 8,239,287,entitled “System for Detecting Probabilistic Associations BetweenItems,” granted Aug. 7, 2012, which is incorporated by reference in itsentirety as if set forth fully herein.

Moving on to box 316, the query classification application 219determines whether the calculated probability “P,” as described inequation 1, exceeds a previously defined threshold value. The previouslydefined threshold value may be set based on empirical observations ofuser behavior. Generally, the threshold value will be one that is highenough that misclassifications will be avoided or minimized, but not sohigh as to cause valid classifications to be overlooked. If thecalculated probability exceeds the previously defined threshold, thenthe previously described path of execution proceeds to box 319.Otherwise, the previously described path of execution subsequently ends.

Proceeding to box 319, the query classification application 219 assignsa search query category 239 to the submitted search query 249 and storesthe requested network page 246 as a suggested network page 243 for thenewly classified search query 226. The search query category 239 may bebased at least in part on the requested network page 246. For example,if the requested network page 246 is for a particular portion orfunctionality of the electronic commerce application 216, such as a helpsection, an account management section, or other portion of theelectronic commerce application 216, then a corresponding search querycategory 239, such as “help query,” “account query,” or a more general“non-product query” search query category 239 may be selected. Thepreviously described path of execution subsequently ends.

Turning now to FIG. 4, shown is a flowchart that provides one example ofthe operation of a portion of the network page server application 223according to various embodiments. It is understood that the flowchart ofFIG. 4 provides merely an example of the many different types offunctional arrangements that may be employed to implement the operationof the portion of the network page server application 223 as describedherein. As an alternative, the flowchart of FIG. 4 may be viewed asdepicting an example of elements of a method implemented in thecomputing environment 203 (FIG. 2) according to one or more embodiments.

Beginning with box 403, network page server application 223 determinesthe classification of the search query category 239 (FIG. 2) of asubmitted search query 249 (FIG. 2). The network page server application223 may, for example, compare the submitted search query 249 with a listof classified search queries 226 (FIG. 2). If the submitted search query249 matches one of the classified search queries 226, then the networkpage server application 223 uses the search query category 239 of thematching classified search query 226. If the submitted search query 249does not match any of the classified search queries 226, then thenetwork page server application 223 may use a default search querycategory 239. For example, in some embodiments, the default search querycategory 239 may correspond to a “product search query” or similar querytype indicating that submitted search query 249 is a search query foritems 253 (FIG. 2) in the product catalog 236 (FIG. 2).

Moving on to box 406, the network page server application 223 identifiescontent for network page responsive to the submitted search query 249.The content may be specified, for example, by a network page template233 used to generate network pages. For example, the network page serverapplication 223 may identify a network page template 233 based on thesearch query category 239 as previously determined. In otherembodiments, the network page template 233 may specify that certaincontent be included in the generated network page based upon the searchquery category 239, as previously determined. In other embodiments, thenetwork page server application 223 may use the suggested network page243 for the response to the submitted search query 249 instead ofgenerating a responsive network page according to the specifications ofa network page template 233.

Proceeding next to box 409, the network page server application 223generates a network page. In some embodiments, the network page serverapplication 223 may simply use the suggested network page 243 associatedwith the search query category 239 as previously determined. In otherembodiments, the network page server application 223 may dynamicallygenerate a network page in the manner specified by the network pagetemplate 233.

Referring next to box 413, the network page server application 223 sendsthe generated network page to the client application 206. The networkpage may be sent, for example, using a version of the hypertext transferprotocol (HTTP) or similar data transfer protocol. The previouslydescribed path of execution subsequently ends.

With reference to FIG. 5, shown is a schematic block diagram of thecomputing environment 203 according to an embodiment of the presentdisclosure. The computing environment 203 includes one or more computingdevices 500. Each computing device 500 includes at least one processorcircuit, for example, having a processor 503 and a memory 506, both ofwhich are coupled to a local interface 509. To this end, each computingdevice 500 may comprise, for example, at least one server computer orlike device. The local interface 509 may comprise, for example, a databus with an accompanying address/control bus or other bus structure ascan be appreciated.

Stored in the memory 506 are both data and several components that areexecutable by the processor 503. In particular, stored in the memory 506and executable by the processor 503 are the electronic commerceapplication 216, the query classification application 219, the networkpage server application 223, and potentially other applications. Alsostored in the memory 506 may be a data store 213 and other data. Inaddition, an operating system may be stored in the memory 506 andexecutable by the processor 503.

It is understood that there may be other applications that are stored inthe memory 506 and are executable by the processor 503 as can beappreciated. Where any component discussed herein is implemented in theform of software, any one of a number of programming languages may beemployed such as, for example, C, C++, C#, Objective C, Java®,JavaScript®, Perl, PHP, Visual Basic®, Python®, Ruby, Flash®, or otherprogramming languages.

A number of software components are stored in the memory 506 and areexecutable by the processor 503. In this respect, the term “executable”means a program file that is in a form that can ultimately be run by theprocessor 503. Examples of executable programs may be, for example, acompiled program that can be translated into machine code in a formatthat can be loaded into a random access portion of the memory 506 andrun by the processor 503, source code that may be expressed in properformat such as object code that is capable of being loaded into a randomaccess portion of the memory 506 and executed by the processor 503, orsource code that may be interpreted by another executable program togenerate instructions in a random access portion of the memory 506 to beexecuted by the processor 503, etc. An executable program may be storedin any portion or component of the memory 506 including, for example,random access memory (RAM), read-only memory (ROM), hard drive,solid-state drive, USB flash drive, memory card, optical disc such ascompact disc (CD) or digital versatile disc (DVD), floppy disk, magnetictape, or other memory components.

The memory 506 is defined herein as including both volatile andnonvolatile memory and data storage components. Volatile components arethose that do not retain data values upon loss of power. Nonvolatilecomponents are those that retain data upon a loss of power. Thus, thememory 506 may comprise, for example, random access memory (RAM),read-only memory (ROM), hard disk drives, solid-state drives, USB flashdrives, memory cards accessed via a memory card reader, floppy disksaccessed via an associated floppy disk drive, optical discs accessed viaan optical disc drive, magnetic tapes accessed via an appropriate tapedrive, and/or other memory components, or a combination of any two ormore of these memory components. In addition, the RAM may comprise, forexample, static random access memory (SRAM), dynamic random accessmemory (DRAM), or magnetic random access memory (MRAM) and other suchdevices. The ROM may comprise, for example, a programmable read-onlymemory (PROM), an erasable programmable read-only memory (EPROM), anelectrically erasable programmable read-only memory (EEPROM), or otherlike memory device.

Also, the processor 503 may represent multiple processors 503 and/ormultiple processor cores and the memory 506 may represent multiplememories 506 that operate in parallel processing circuits, respectively.In such a case, the local interface 509 may be an appropriate networkthat facilitates communication between any two of the multipleprocessors 503, between any processor 503 and any of the memories 506,or between any two of the memories 506, etc. The local interface 509 maycomprise additional systems designed to coordinate this communication,including, for example, performing load balancing. The processor 503 maybe of electrical or of some other available construction.

Although the electronic commerce application 216, the queryclassification application 219, the network page server application 223,and other various systems described herein may be embodied in softwareor code executed by general purpose hardware as discussed above, as analternative the same may also be embodied in dedicated hardware or acombination of software/general purpose hardware and dedicated hardware.If embodied in dedicated hardware, each can be implemented as a circuitor state machine that employs any one of or a combination of a number oftechnologies. These technologies may include, but are not limited to,discrete logic circuits having logic gates for implementing variouslogic functions upon an application of one or more data signals,application specific integrated circuits (ASICs) having appropriatelogic gates, field-programmable gate arrays (FPGAs), or othercomponents, etc. Such technologies are generally well known by thoseskilled in the art and, consequently, are not described in detailherein.

The flowcharts of FIGS. 3 and 4 show the functionality and operation ofan implementation of portions of the query classification application219 and the network page server application 223 s. If embodied insoftware, each block may represent a module, segment, or portion of codethat comprises program instructions to implement the specified logicalfunction(s). The program instructions may be embodied in the form ofsource code that comprises human-readable statements written in aprogramming language or machine code that comprises numericalinstructions recognizable by a suitable execution system such as aprocessor 503 in a computer system or other system. The machine code maybe converted from the source code, etc. If embodied in hardware, eachblock may represent a circuit or a number of interconnected circuits toimplement the specified logical function(s).

Although the flowcharts of FIGS. 3 and 4 show a specific order ofexecution, it is understood that the order of execution may differ fromthat which is depicted. For example, the order of execution of two ormore blocks may be scrambled relative to the order shown. Also, two ormore blocks shown in succession in FIGS. 3 and 4 may be executedconcurrently or with partial concurrence. Further, in some embodiments,one or more of the blocks shown in FIGS. 3 and 4 may be skipped oromitted. In addition, any number of counters, state variables, warningsemaphores, or messages might be added to the logical flow describedherein, for purposes of enhanced utility, accounting, performancemeasurement, or providing troubleshooting aids, etc. It is understoodthat all such variations are within the scope of the present disclosure.

Also, any logic or application described herein, including theelectronic commerce application 216, the query classificationapplication 219, and the network page server application 223, thatcomprises software or code can be embodied in any non-transitorycomputer-readable medium for use by or in connection with an instructionexecution system such as, for example, a processor 503 in a computersystem or other system. In this sense, the logic may comprise, forexample, statements including instructions and declarations that can befetched from the computer-readable medium and executed by theinstruction execution system. In the context of the present disclosure,a “computer-readable medium” can be any medium that can contain, store,or maintain the logic or application described herein for use by or inconnection with the instruction execution system.

The computer-readable medium can comprise any one of many physical mediasuch as, for example, magnetic, optical, or semiconductor media. Morespecific examples of a suitable computer-readable medium would include,but are not limited to, magnetic tapes, magnetic floppy diskettes,magnetic hard drives, memory cards, solid-state drives, USB flashdrives, or optical discs. Also, the computer-readable medium may be arandom access memory (RAM) including, for example, static random accessmemory (SRAM) and dynamic random access memory (DRAM), or magneticrandom access memory (MRAM). In addition, the computer-readable mediummay be a read-only memory (ROM), a programmable read-only memory (PROM),an erasable programmable read-only memory (EPROM), an electricallyerasable programmable read-only memory (EEPROM), or other type of memorydevice.

Further, any logic or application described herein, including theelectronic commerce application 216, the query classificationapplication 219, and the network page server application 223, may beimplemented and structured in a variety of ways. For example, one ormore applications described may be implemented as modules or componentsof a single application. Further, one or more applications describedherein may be executed in shared or separate computing devices or acombination thereof. For example, a plurality of the applicationsdescribed herein may execute in the same computing device 500, or inmultiple computing devices in the same computing environment 203.Additionally, it is understood that terms such as “application,”“service,” “system,” “engine,” “module,” and so on may beinterchangeable and are not intended to be limiting.

Disjunctive language such as the phrase “at least one of X, Y, or Z,”unless specifically stated otherwise, is otherwise understood with thecontext as used in general to present that an item, term, etc., may beeither X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z).Thus, such disjunctive language is not generally intended to, and shouldnot, imply that certain embodiments require at least one of X, at leastone of Y, or at least one of Z to each be present.

It should be emphasized that the above-described embodiments of thepresent disclosure are merely possible examples of implementations setforth for a clear understanding of the principles of the disclosure.Many variations and modifications may be made to the above-describedembodiment(s) without departing substantially from the spirit andprinciples of the disclosure. All such modifications and variations areintended to be included herein within the scope of this disclosure andprotected by the following claims.

Therefore, the following is claimed:
 1. A system, comprising: acomputing device comprising a processor and a memory; and an applicationcomprising machine readable instructions stored in the memory that, whenexecuted by the processor, cause the computing device to at least:determine a classification of a search query submitted to the computingdevice, wherein the classification of the search query is based at leastin part on a probability that a type of network page will be requestedsubsequent to a submission of the search query; and generate a networkpage in response to a submission of the search query, wherein at least aportion of the content of the network page is based at least in part onthe classification of the submitted search query.
 2. The system of claim1, wherein the machine readable instructions that cause the computingdevice to generate the network page in response to the submission of thesearch query further comprise machine readable instructions that causethe computing device to at least: identify content associated withclassification of the search query; and incorporate the contentassociated with the classification of the search query into the networkpage.
 3. The method of claim 2, wherein the content associated with theclassification of the search query comprises a recommended network page.4. The system of claim 3, wherein the recommended network page has ahigher probability of being requested after submission of the searchquery in comparison to a probability that an unrecommended network pagewill be requested after submission of the search query.
 5. The system ofclaim 1, wherein the machine readable instructions that cause thecomputing device to determine the classification of the search queryfurther comprise machine readable instructions that, when executed bythe computing device, cause the computing device to at least: match thesearch query to at least one of a plurality of previously classifiedsearch queries; and identify the classification that matches the atleast one of the plurality of previously classified search queries. 6.The system of claim 1, wherein the network page comprises a firstnetwork page and wherein the search query is submitted to the computingdevice via a search bar within a second network page.
 7. The system ofclaim 1, wherein the classification of the search query comprises atleast one of a non-product search query or a product search query. 8.The system of claim 1, wherein the machine readable instructions, whenexecuted by the processor, further cause the computing device to atleast calculate a ratio of an expected number of requests for the typeof network page compared to an observed number of requests for the typeof network page occurring after the submission of the search query. 9.The system of claim 8, wherein the probability that the type of networkpage that will be requested subsequent to the submission of the searchquery is based at least in part on the ratio of the expected number ofrequests for the type of network page compared to the observed number ofrequests for the type of network page occurring after the submission ofthe search query.
 10. A method, comprising: determining, via a computingdevice, a classification of a search query submitted to the computingdevice, wherein the classification of the search query is based at leastin part on a probability that a type of network page will be requestedsubsequent to a submission of the search query; and generating, via thecomputing device, a network page in response to a submission of thesearch query, wherein at least a portion of the content of the networkpage is based at least in part on the classification of the submittedsearch query.
 11. The method of claim Error! Bookmark not defined.0,wherein generating the network page in response to the submission of thesearch query further comprises: identifying, via the computing device,content associated with classification of the search query; andincorporating, via the computing device, the content associated with theclassification of the search query into the network page.
 12. The methodof claim 11, wherein the content associated with the classification ofthe search query comprises a recommended network page.
 13. The method ofclaim 12, wherein the recommended network page has a higher probabilityof being requested after submission of the search query in comparison toa probability that an unrecommended network page will be requested aftersubmission of the search query.
 14. The method of claim 10, whereindetermining the classification of the search query further comprises:matching, via the computing device, the search query to at least one ofa plurality of previously classified search queries; and identifying,via the computing device, the classification that matches the at leastone of the plurality of previously classified search queries.
 15. Themethod of claim 10, wherein the network page comprises a first networkpage and wherein the search query is submitted to the computing devicevia a search bar within a second network page.
 16. The method of claim10, wherein the classification of the search query comprises at leastone of a non-product search query or a product search query.
 17. Themethod of claim 10, wherein the probability that the type of networkpage that will be requested subsequent to the submission of the searchquery is determined at least in part by calculating, via the computingdevice, a ratio of an expected number of requests for the type ofnetwork page compared to an observed number of requests for the type ofnetwork page occurring after the submission of the search query.
 18. Asystem, comprising: a computing device comprising a processor and amemory; and an application comprising machine readable instructionsstored in the memory that, when executed by the processor, cause thecomputing device to at least: match a search query to at least one of aplurality of previously classified search queries; identify aclassification that matches the at least one of the plurality ofpreviously classified search queries; assign to the search query theclassification that matches the at least one of the plurality ofpreviously classified search queries; identify content associated withclassification; generate a network page in response to a submission ofthe search query, wherein at least a portion of the content of thenetwork page is based at least in part on the classification; andincorporate the content associated with the classification of the searchquery into the network page.
 19. The system of claim 18, wherein thecontent associated with the classification of the search query comprisesa recommended network page.
 20. The system of claim 18, wherein therecommended network page has a higher probability of being requestedafter submission of the search query in comparison to a probability thatan unrecommended network page will be requested after submission of thesearch query.